scholarly journals Genome-wide association mapping and genomic prediction for adult stage sclerotinia stem rot resistance in Brassica napus (L) under field environments

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jayanta Roy ◽  
T. M. Shaikh ◽  
Luis del Río Mendoza ◽  
Shakil Hosain ◽  
Venkat Chapara ◽  
...  
Keyword(s):  
Genomic Prediction ◽  
Predictive Ability ◽  
Significant Snps ◽  
Genome Wide Association ◽  
Stem Rot ◽  
Lesion Length ◽  
Sclerotinia Stem Rot ◽  
Agar Plug ◽  
Genome Wide ◽  
Full Flowering

AbstractSclerotinia stem rot (SSR) is a fungal disease of rapeseed/canola that causes significant seed yield losses and reduces its oil content and quality. In the present study, the reaction of 187 diverse canola genotypes to SSR was characterized at full flowering stage using the agar plug to stem inoculation method in four environments. Genome-wide association study (GWAS) using three different algorithms identified 133 significant SNPs corresponding with 123 loci for disease traits like stem lesion length (LL), lesion width (LW), and plant mortality at 14 (PM_14D) and 21 (PM_21D) days. The explained phenotypic variation of these SNPs ranged from 3.6 to 12.1%. Nineteen significant SNPs were detected in two or more environments, disease traits with at least two GWAS algorithms. The strong correlations observed between LL and other three disease traits evaluated, suggest they could be used as proxies for SSR resistance phenotyping. Sixty-nine candidate genes associated with disease resistance mechanisms were identified. Genomic prediction (GP) analysis with all the four traits employing genome-wide markers resulted in 0.41–0.64 predictive ability depending on the model specifications. The highest predictive ability for PM_21D with three models was about 0.64. From our study, the identified resistant genotypes and stable significant SNP markers will serve as a valuable resource for future SSR resistance breeding. Our study also suggests that genomic selection holds promise for accelerating canola breeding progress by enabling breeders to select SSR resistance genotypes at the early stage by reducing the need to phenotype large numbers of genotypes.

scholarly journals Genome-Wide Association Mapping and Genomic Prediction for Adult Stage Sclerotinia Stem Rot Resistance in Brassica Napus (L) Under Field Environments

2021 ◽  
Author(s):  
Jayanta Roy ◽  
T M Shaikh ◽  
Luis E. del Río Mendoza ◽  
Shakil Hosain ◽  
Venkat Chapara ◽  
...  
Keyword(s):  
Genomic Prediction ◽  
Significant Snps ◽  
Genome Wide Association ◽  
Stem Rot ◽  
Lesion Length ◽  
Sclerotinia Stem Rot ◽  
Agar Plug ◽  
Genome Wide ◽  
Full Flowering ◽  
Gp Model

Abstract Sclerotinia stem rot (SSR) is a fungal disease of rapeseed/canola that causes significant seed yield losses and reduces its oil content and quality. In the present study, the reaction of 187 diverse canola genotypes to SSR was characterized at full flowering stage using the agar plug to stem inoculation method in four environments. Genome-wide association study (GWAS) using three different algorithms identified 133 significant SNPs corresponding with 123 loci for disease traits like stem lesion length (LL), lesion width (LW), and plant mortality at 14 (PM_14D) and 21 (PM_21D) days. The explained phenotypic variation of these SNPs ranged from 3.6–12.1%. Nineteen significant SNPs were detected in two or more environments, disease traits with at least two GWAS algorithms. The strong correlations observed between LL and other three disease traits evaluated, suggest they could be used as proxies for SSR resistance phenotyping. Sixty-nine candidate genes associated with disease resistance mechanisms were identified. Genomic prediction (GP) analysis with all the four traits employing genome-wide markers resulted in 0.43–0.63 prediction accuracy. However, the prediction efficiency was further improved 0.55–0.88 when we integrated the GWAS information in the GP model. From our study, the identified resistant genotypes and stable significant SNP markers will serve as a valuable resource for future SSR resistance breeding. Our study also suggests that genomic selection holds promise for accelerating canola breeding progress by enabling breeders to select SSR resistance genotypes at the early stage by reducing the need to phenotype large numbers of genotypes.

scholarly journals Genetic Mapping and Genomic Prediction of Sclerotinia Stem Rot Resistance to Rapeseed/Canola (Brassica Napus L.) at Seedling Stage

2021 ◽  
Author(s):  
Jayanta Roy ◽  
Luis E. del Río Mendoza ◽  
Nonoy Bandillo ◽  
Phillip E. McClean ◽  
Mukhlesur Rahman
Keyword(s):  
Genomic Prediction ◽  
Predictive Ability ◽  
Resistance Breeding ◽  
Significant Snps ◽  
Stem Rot ◽  
Post Inoculation ◽  
Phenotypic Variance ◽  
Sclerotinia Stem Rot ◽  
Brassica Napus L ◽  
Genome Wide

Abstract The lack of complete host resistance and a complex resistance inheritance nature between rapeseed/canola and Sclerotinia sclerotiorum often limits the development of functional molecular markers that enable breeding for sclerotinia stem rot (SSR) resistance. However, genomics-assisted selection has the potential to accelerate the breeding for SSR resistance. Therefore, genome-wide association (GWA) mapping and genomic prediction (GP) was performed using a diverse panel of 337 rapeseed/canola genotypes. Three-weeks old seedlings were screened using the petiole inoculation technique (PIT). Days to wilt (DW) up to 2 weeks and lesion phenotypes (LP) at 3, 4, and 7 days post inoculation (dpi) were recorded. A strong correlation (r = -0.94) between DW and LP_4dpi implied that a single time point scoring at four days could be used as a proxy trait. GWA analyses using single-locus (SL) and multi-locus (ML) models identified a total of 35, and 219 significantly associated SNPs, respectively. Out of these, seventy-one SNPs were identified by a combination of the SL model and any of the ML models, at least two ML models, or two traits. These SNPs explained 1.4-13.3% of the phenotypic variance, and considered as significant, could be associated with SSR resistance. Eighty-one candidate genes with a function in disease resistance were associated with the significant SNPs. Six GP models resulted in moderate to high (0.45-0.68) predictive ability depending on SSR resistance traits. The resistant genotypes and significant SNPs will serve as valuable resources for future SSR resistance breeding. Our results also highlight the potential of genomic selection to improve rapeseed/canola breeding for SSR resistance.

scholarly journals Modeling first order additive × additive epistasis improves accuracy of genomic prediction for sclerotinia stem rot resistance in canola

2021 ◽  
Author(s):  
Mark C Derbyshire ◽  
Yuphin Khentry ◽  
Anita Severn‐Ellis ◽  
Virginia Mwape ◽  
Nur Shuhadah Mohd Saad ◽  
...  
Keyword(s):  
Genomic Prediction ◽  
Stem Rot ◽  
Sclerotinia Stem Rot ◽  
First Order

scholarly journals A Genome-Wide Association Study To Understand the Effect of Fusarium verticillioides Infection on Seedlings of a Maize Diversity Panel

2020 ◽  
Vol 10 (5) ◽  
pp. 1685-1696
Author(s):  
Lorenzo Stagnati ◽  
Vahid Rahjoo ◽  
Luis F. Samayoa ◽  
James B. Holland ◽  
Virginia M. G. Borrelli ◽  
...  
Keyword(s):  
Association Study ◽  
Genome Wide Association Study ◽  
Germination Rate ◽  
Fusarium Verticillioides ◽  
Screening Method ◽  
Significant Snps ◽  
Genome Wide Association ◽  
Genome Wide ◽  
Seedling Length ◽  
A Genome

Fusarium verticillioides, which causes ear, kernel and stem rots, has been reported as the most prevalent species on maize worldwide. Kernel infection by F. verticillioides results in reduced seed yield and quality as well as fumonisin contamination, and may affect seedling traits like germination rate, entire plant seedling length and weight. Maize resistance to Fusarium is a quantitative and complex trait controlled by numerous genes with small effects. In the present work, a Genome Wide Association Study (GWAS) of traits related to Fusarium seedling rot was carried out in 230 lines of a maize association population using 226,446 SNP markers. Phenotypes were scored on artificially infected kernels applying the rolled towel assay screening method and three traits related to disease response were measured in inoculated and not-inoculated seedlings: plant seedling length (PL), plant seedling weight (PW) and germination rate (GERM). Overall, GWAS resulted in 42 SNPs significantly associated with the examined traits. Two and eleven SNPs were associated with PL in inoculated and not-inoculated samples, respectively. Additionally, six and one SNPs were associated with PW and GERM traits in not-inoculated kernels, and further nine and thirteen SNPs were associated to the same traits in inoculated kernels. Five genes containing the significant SNPs or physically closed to them were proposed for Fusarium resistance, and 18 out of 25 genes containing or adjacent to significant SNPs identified by GWAS in the current research co-localized within QTL regions previously reported for resistance to Fusarium seed rot, Fusarium ear rot and fumonisin accumulation. Furthermore, linkage disequilibrium analysis revealed an additional gene not directly observed by GWAS analysis. These findings could aid to better understand the complex interaction between maize and F. verticillioides.

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